948 citations · 1.3k across the 13 of their papers we have counts for
13 papers
Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective Method
Yixuan Li, Bolin Chen, Baoliang Chen +3
Recent years have witnessed an exponential increase in the demand for face video compression, and the success of artificial intelligence has expanded the boundaries beyond traditio…
Gap-closing Matters: Perceptual Quality Evaluation and Optimization of Low-Light Image Enhancement
Baoliang Chen, Lingyu Zhu, Hanwei Zhu +3
There is a growing consensus in the research community that the optimization of low-light image enhancement approaches should be guided by the visual quality perceived by end users…
DeepDC: Deep Distance Correlation as a Perceptual Image Quality Evaluator
Hanwei Zhu, Baoliang Chen, Lingyu Zhu +2
ImageNet pre-trained deep neural networks (DNNs) show notable transferability for building effective image quality assessment (IQA) models. Such a remarkable byproduct has often be…
High Dynamic Range Image Quality Assessment Based on Frequency Disparity
Yue Liu, Zhangkai Ni, Shiqi Wang +2
In this paper, a novel and effective image quality assessment (IQA) algorithm based on frequency disparity for high dynamic range (HDR) images is proposed, termed as local-global f…
Learning from Mixed Datasets: A Monotonic Image Quality Assessment Model
Zhaopeng Feng, Keyang Zhang, Shuyue Jia +2
Deep learning based image quality assessment (IQA) models usually learn to predict image quality from a single dataset, leading the model to overfit specific scenes. To account for…
Deep Feature Statistics Mapping for Generalized Screen Content Image Quality Assessment
Baoliang Chen, Hanwei Zhu, Lingyu Zhu +2
The statistical regularities of natural images, referred to as natural scene statistics, play an important role in no-reference image quality assessment. However, it has been widel…
The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement
Danni Huang, Lingyu Zhu, Zihao Lin +3
There is an increasing consensus that the design and optimization of low light image enhancement methods need to be fully driven by perceptual quality. With numerous approaches pro…
Locally Adaptive Structure and Texture Similarity for Image Quality Assessment
Keyan Ding, Yi Liu, Xueyi Zou +2
The latest advances in full-reference image quality assessment (IQA) involve unifying structure and texture similarity based on deep representations. The resulting Deep Image Struc…
No-Reference Image Quality Assessment by Hallucinating Pristine Features
Baoliang Chen, Lingyu Zhu, Chenqi Kong +3
In this paper, we propose a no-reference (NR) image quality assessment (IQA) method via feature level pseudo-reference (PR) hallucination. The proposed quality assessment framework…
Comparison of Image Quality Models for Optimization of Image Processing Systems
Keyan Ding, Kede Ma, Shiqi Wang +1
The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human quality judgments. Perceptual datasets gathe…
Image Quality Assessment: Unifying Structure and Texture Similarity
Keyan Ding, Kede Ma, Shiqi Wang +1
Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original. Relative to human observers, these measures are overly sen…
Single Image Deraining: From Model-Based to Data-Driven and Beyond
Wenhan Yang, Robby T. Tan, Shiqi Wang +2
The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation. The early single-image deraining method…
Intrinsic Image Popularity Assessment
Keyan Ding, Kede Ma, Shiqi Wang
The goal of research in automatic image popularity assessment (IPA) is to develop computational models that can accurately predict the potential of a social image to go viral on th…